An effort to improve wind power energy has been continuously conducted over the world, and a high increase trend of a wind power generation facility capacity of 26.5% on the average has been continued for the past five years.
In 2011, a global wind power generation facility capacity arrives at 241 GW. However, European and American countries as well as Korea have continuously raised a wind power energy supplying target.
In order to accomplish the supplying target as described above, it has become the most important current challenge to find new places in which wind power generators are to be installed. Therefore, each country has conducted an effort to make a wind power resource map more precise than an existing wind power resource map to secure new candidates in which wind power generators are to be installed.
As a current development trend of the wind power resource map, computational fluid dynamics numerical simulation that may accurately reflect a terrain effect in order to increase a spatial resolution of the wind power resource map has been adopted. However, the computational fluid dynamics numerical simulation has a problem that a large calculation load and calculation time are required.
This trend is common in various fields using atmospheric wind flow information, such as construction wind engineering, forest fire diffusion prediction, air pollution diffusion, aviation safety evaluation, and the like, as well as the wind power resource map.
Therefore, as a typical case, making a wind power resource map will be described in detail as an example.
First, in the case in which appropriateness evaluation for building a wind power generation farm is performed by actual measurement, a wind condition tower having a height corresponding to ⅔ or more of a hub height of a wind power generator and including a plurality of anemometers in a height direction is installed and used.
Here, measurement for at least one year or more by the respective anemometers is required, it is required to correct this by a wind speed at an actual hub height, and this should be corrected for twenty years or more, which is a design lifespan of the wind power generator.
In order to solve a problem that a time required for this measurement and analysis is increased and further increase analysis reliability in a wide area, it is required to make a wind power resource map by an atmospheric wind flow numerical simulation.
A typical example of an atmospheric wind flow modeling method for making the wind power resource map may include the following two methods.
A first method, which is a method of using a linear theory model of an atmospheric wind flow by Jackon and Hunt, is appropriate for a flat region in which a terrain change is hardly present.
That is, the first method cannot but be very inaccurate in a terrain having many mountain regions (terrain in which an inclination and a change rate of a local terrain are large) such as Korea.
A second method, which is a method of using a computational wind flow analysis method, has an advantage that an accurate numerical simulation of atmospheric wind flow change characteristics by a terrain is possible.
That is, meteorological variables such as all wind directions, wind speeds, atmosphere stabilities, and the like, that may be meteorologically generated are imposed as individual boundary conditions to numerically simulate an analysis area by computational fluid dynamics numerical simulation system, and an appearance frequency for each wind direction, an appearance frequency for each wind speed, an appearance frequency for each atmosphere stability, and the like, calculated from reliable actually measured data obtained from the wind condition tower are applied as a weight to overlap all meteorological examples with each other, thereby making it possible to make a space distribution of a meteorological-statistically averaged atmospheric wind flow, that is, the wind power resource map.
Here, generally, in a numerical simulation method of an atmospheric wind flow, in the case of a numerical simulation of a middle scale atmospheric wind flow having a size of several hundred kilometers, a time sequential continuous analysis is performed to numerically analyze a process of changing an atmospheric wind flow by a change in solar radiation, or the like, and in the case of a numerical simulation of a microscopic scale atmospheric wind flow having a size of several ten kilometers, a scheme of individually numerically analyzing normal state atmospheric wind flows for each meteorological variable using a dynamic downscaling method and applying a statistical appearance frequency of meteorological variables as a weight to perform overlap is used.
Here, in order to further increase reliability of the wind power resource map, an atmospheric wind flow numerical simulation for all generable meteorological states such as a wind direction, a wind speed, an atmosphere stability, and the like, of synoptic wind or local wind having an influence on an analysis area is required. However, there is a problem that a large amount of calculation load and calculation time cannot but be required in order to analyze all generable meteorological states.
As a wind resource mapping method using a atmospheric wind flow numerical simulation system, which is the above-mentioned second method, Korean Patent Laid-Open Publication No. 10-2005-0063616 (entitled “Wind Resource Mapping Method” and published on Jun. 28, 2005) and Korean Patent Laid-Open Publication No. 10-2011-0099509 (entitled “Wind Resources Mapping System and Method”) have been suggested.